Social and spatial effects on genetic variation between foraging flocks in a wild bird population

Social interactions are rarely random. In some instances, animals exhibit homophily or heterophily, the tendency to interact with similar or dissimilar conspecifics, respectively. Genetic homophily and heterophily influence the evolutionary dynamics of populations, because they potentially affect sexual and social selection. Here, we investigate the link between social interactions and allele frequencies in foraging flocks of great tits (Parus major ) over three consecutive years. We constructed co‐occurrence networks which explicitly described the splitting and merging of 85,602 flocks through time (fission–fusion dynamics), at 60 feeding sites. Of the 1,711 birds in those flocks, we genotyped 962 individuals at 4,701 autosomal single nucleotide polymorphisms (SNP s). By combining genomewide genotyping with repeated field observations of the same individuals, we were able to investigate links between social structure and allele frequencies at a much finer scale than was previously possible. We explicitly accounted for potential spatial effects underlying genetic structure at the population level. We modelled social structure and spatial configuration of great tit fission–fusion dynamics with eigenvector maps. Variance partitioning revealed that allele frequencies were strongly affected by group fidelity (explaining 27%–45% of variance) as individuals tended to maintain associations with the same conspecifics. These conspecifics were genetically more dissimilar than expected, shown by genomewide heterophily for pure social (i.e., space‐independent) grouping preferences. Genomewide homophily was linked to spatial configuration, indicating spatial segregation of genotypes. We did not find evidence for homophily or heterophily for putative socially relevant candidate genes or any other SNP markers. Together, these results demonstrate the importance of distinguishing social and spatial processes in determining population structure

Connecting the data landscape of long-term ecological studies: The SPI-Birds data hub

The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long-term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad-scale global issues (e.g. climate change). To solve data integration issues and enable a new scale of ecological and evolutionary research based on long-term studies of birds, we have created the SPI-Birds Network and Database (www.spibirds.org)\u2014a large-scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI-Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting. SPI-Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community-derived data and meta-data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta-data language). The encouraging community involvement stems from SPI-Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI-Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community-specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much-needed large-scale ecological data integration

Search for Neutrinoless Double- β Decay with the Complete EXO-200 Dataset

A search for neutrinoless double-β decay (0νββ) in Xe136 is performed with the full EXO-200 dataset using a deep neural network to discriminate between 0νββ and background events. Relative to previous analyses, the signal detection efficiency has been raised from 80.8% to 96.4±3.0%, and the energy resolution of the detector at the Q value of Xe136 0νββ has been improved from σ/E=1.23% to 1.15±0.02% with the upgraded detector. Accounting for the new data, the median 90% confidence level 0νββ half-life sensitivity for this analysis is 5.0×1025 yr with a total Xe136 exposure of 234.1 kg yr. No statistically significant evidence for 0νββ is observed, leading to a lower limit on the 0νββ half-life of 3.5×1025 yr at the 90% confidence level

The Sudbury Neutrino Observatory

The Sudbury Neutrino Observatory is a second generation water Cherenkov detector designed to determine whether the currently observed solar neutrino deficit is a result of neutrino oscillations. The detector is unique in its use of D2O as a detection medium, permitting it to make a solar model-independent test of the neutrino oscillation hypothesis by comparison of the charged- and neutral-current interaction rates. In this paper the physical properties, construction, and preliminary operation of the Sudbury Neutrino Observatory are described. Data and predicted operating parameters are provided whenever possible.Comment: 58 pages, 12 figures, submitted to Nucl. Inst. Meth. Uses elsart and epsf style files. For additional information about SNO see http://www.sno.phy.queensu.ca . This version has some new reference

Social organisation of thornbill-dominated mixed-species flocks using social network analysis

Mixed-species associations are a widespread phenomenon, comprising interacting heterospecific individuals which gain predator, foraging or social benefits. Avian flocks have traditionally been classified as monolithic species units, with species-wide functional roles, such as nuclear, active, passive, or follower. It has also been suggested that flocks are mutualistic interactions, where niches of participating species converge. However the species-level perspective has limited previous studies, because both interactions and benefits occur at the level of the individual. Social network analysis provides a set of tools for quantitative assessment of individual participation. We used mark-resighting methods to develop networks of nodes (colour-marked individuals) and edges (their interactions within flocks). We found that variation in flock participation across individuals within species, especially in the buff-rumped thornbill, encompassed virtually the entire range of variation across all individuals in the entire set of species. For example, female, but not male, buff-rumped thornbills had high network betweenness, indicating that they interact with multiple flocks, likely as part of a female-specific dispersal strategy. Finally, we provide new evidence that mixed-species flocking is mutualistic, by quantifying an active shift in individual foraging niches towards those of their individual associates, with implications for trade-off between costs and benefits to individuals derived from participating in mixed-species flocks. This study is, to our knowledge, the first instance of a heterospecific social network built on pairwise interactions

Three Twentieth Century English Song Composers: Peter Warlock, E. J. Moeran and John Ireland

313 p.Thesis (D.Mus.A.)--University of Illinois at Urbana-Champaign, 1969.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

The role of social and ecological processes in structuring animal populations : A case study from automated tracking of wild birds

Both social and ecological factors influence population process and structure, with resultant consequences for phenotypic selection on individuals. Understanding the scale and relative contribution of these two factors is thus a central aim in evolutionary ecology. In this study, we develop a framework using null models to identify the social and spatial patterns that contribute to phenotypic structure in a wild population of songbirds. We used automated technologies to track 1053 individuals that formed 73 737 groups from which we inferred a social network. Our framework identified that both social and spatial drivers contributed to assortment in the network. In particular, groups had a more even sex ratio than expectedand exhibited a consistent age structure that suggested local association preferences, such as preferential attachment or avoidance. By contrast, recent immigrants were spatially partitioned from locally born individuals, suggesting differential dispersal strategies by phenotype. Our results highlight how different scales of social decision-making, ranging from post-natal dispersal settlement to fission–fusion dynamics, can interact to drive phenotypic structure in animal populations.</p

Social barriers in ecological landscapes: the social resistance hypothesis

Across animal societies, individuals invest time and energy in social interactions. The social landscape that emerges from these interactions can then generate barriers that limit the ability of individuals to disperse to, and reproduce in, groups or populations. Therefore, social barriers can contribute to the difference between the physical capacity for movement through the habitat and subsequent gene flow. We call this contributing effect ‘social resistance’. We propose that social resistance can act as an agent of selection on key life-history strategies and promote the evolution of social strategies that facilitate effective dispersal. By linking landscape genetics and social behaviour, the social resistance hypothesis generates predictions integrating dispersal, connectivity, and life-history evolution.Nicolette C.Armansin, Adam J.Stow, Mauricio Cantor, Stephan T.Leu, James A.Klarevas-Irb

Data from: The role of social and ecological processes in structuring animal populations: a case study from automated tracking of wild birds

Both social and ecological factors influence population process and structure, with resultant consequences for phenotypic selection on individuals. Understanding the scale and relative contribution of these two factors is thus a central aim in evolutionary ecology. In this study, we develop a framework using null models to identify the social and spatial patterns that contribute to phenotypic structure in a wild population of songbirds. We used automated technologies to track 1053 individuals that formed 73 737 groups from which we inferred a social network. Our framework identified that both social and spatial drivers contributed to assortment in the network. In particular, groups had a more even sex ratio than expected and exhibited a consistent age structure that suggested local association preferences, such as preferential attachment or avoidance. By contrast, recent immigrants were spatially partitioned from locally born individuals, suggesting differential dispersal strategies by phenotype. Our results highlight how different scales of social decision-making, ranging from post-natal dispersal settlement to fission–fusion dynamics, can interact to drive phenotypic structure in animal populations

Counting conformity: evaluating the units of information in frequency-dependent social learning

In a recent study (Aplin et al., 2015), we conducted a large-scale cultural diffusion experiment in which we used trained ‘demonstrator’ individuals to introduce one of two alternative foraging techniques into five replicate subpopulations of wild great tits, Parus major. Three further subpopulations served as controls. By tracking the spread of these two techniques, we showed that information was acquired through social learning, transmitted through social network ties, and novel behaviours became established in each subpopulation, forming stable arbitrary traditions (for technique A or B). These traditions persisted over generations and were stable despite immigrating and innovating individuals, resulting in a within-group behavioural homogeneity and between-group variation. Most pertinent for this discussion, our experimental design allowed an examination of the interaction between individual decision making and population level outcomes. We found that the population level bias for each introduced technique increased by an average of 14% per day towards the common variant. This was explained both by a tendency for naïve individuals to disproportionately adopt the most common behaviour (‘conformist transmission’) and by a tendency for individuals with experience of both techniques to change their behaviour to match the common variant (‘conformity’)